Dataset Information

Genetic Characterization of Cupped Oyster Resources in Europe Using Informative Single Nucleotide Polymorphism (SNP) Panels.

ABSTRACT: The Pacific oyster, Crassostrea gigas, was voluntarily introduced from Japan and British Columbia into Europe in the early 1970s, mainly to replace the Portuguese oyster, Crassostrea angulata, in the French shellfish industry, following a severe disease outbreak. Since then, the two species have been in contact in southern Europe and, therefore, have the potential to exchange genes. Recent evolutionary genomic works have provided empirical evidence that C. gigas and C. angulata exhibit partial reproductive isolation. Although hybridization occurs in nature, the rate of interspecific gene flow varies across the genome, resulting in highly heterogeneous genome divergence. Taking this biological property into account is important to characterize genetic ancestry and population structure in oysters. Here, we identified a subset of ancestry-informative makers from the most differentiated regions of the genome using existing genomic resources. We developed two different panels in order to (i) easily differentiate C. gigas and C. angulata, and (ii) describe the genetic diversity and structure of the cupped oyster with a particular focus on French Atlantic populations. Our results confirm high genetic homogeneity among Pacific cupped oyster populations in France and reveal several cases of introgressions between Portuguese and Japanese oysters in France and Portugal.

SUBMITTER: Lapegue S

PROVIDER: S-EPMC7230726 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Genetic Characterization of Cupped Oyster Resources in Europe Using Informative Single Nucleotide Polymorphism (SNP) Panels.

Lapègue Sylvie S Heurtebise Serge S Cornette Florence F Guichoux Erwan E Gagnaire Pierre-Alexandre PA

Genes 20200421 4

The Pacific oyster, Crassostrea gigas, was voluntarily introduced from Japan and British Columbia into Europe in the early 1970s, mainly to replace the Portuguese oyster, Crassostrea angulata, in the French shellfish industry, following a severe disease outbreak. Since then, the two species have been in contact in southern Europe and, therefore, have the potential to exchange genes. Recent evolutionary genomic works have provided empirical evidence that C. gigas and C. an ...[more]

PMID: 32326303

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Project description:Dear Editor, The recent article by Mohammadzadeh et al.[1] on the latest issue of this Journal showed that the T allele +276G/T SNP of ADIPOQ gene is more associated with the increasing risk of coronary artery disease (CAD) in subjects with type 2 diabetes. Adipocytes were described in myocardial tissue of CAD patients and their role recently discussed[2,3]. Susceptibility to CAD by polymorphism in the Q gene of adiponectin has been reported for 3'-UTR, which harbours some genetic loci associated with metabolic risks and atherosclerosis[4]. Actually, previous studies have shown that the haplotype SNP +276G>T was associated with a decreased risk of CAD, after adjustment for potential confounding factors, therefore some controversial opinion still exists[5]. This evidence should be associated with the role exerted by adipocytes and adiponectin in heart physiology. In particular, in hypertensive disorder complicating pregnancy (HDCP), by investigating the population frequency of alleles, genotypes, and haplotypes of two single nucleotide polymorphisms (SNPs), namely +45T>G (rs2241766) and +276G>T (rs1501299), some authors found that the SNP +276 TT genotype was significantly associated with protection against HDCP, when compared to the pooled G genotypes[6]. Moreover, the same +276G/T SNP haplotype was strongly associated with biliary atresia, an intractable neonatal inflammatory and obliterative cholangiopathy, leading to progressive fibrosis and cirrhosis[7]. CAD is closely related to adiponectin biology. The same isoforms of adiponectin seem to be not associated to CAD severity but to glucose metabolism and its impairment[8]. In the paper by Mohammadzadeh et al.[1], T allele in +276G/T SNP haplotype is highly associated with CAD in subjects with type 2 diabetes, but this linkage should be reappraised if related much more to diabetes rather than CAD. Association of T allele in the indicated SNP with CAD may be an indirect consequence of type 2 diabetes, as reported by others[9] or a direct marker for CAD affected patients[10]. The paper by Mohammadzadeh et al.[1] assesses data coming elsewhere from literature but raises important concerns about the suitability of ADIPOQ SNPs in diagnosing susceptibility to CAD and the relationship with plasma adiponectin level. In normal, non diabetic, normoglycemic subject, this relationship does not seem to work. Therefore the question is how much predictive this SNP haplotype may be to foresee metabolic syndrome and CAD onset risk in young health subjects? Maybe, the role of adiponectin in cardiovascular physiology depends on its ability to target adiponectin receptors and to negatively regulate obesity. Some authors reported in healthy volunteers an absence of correlation between circulating adiponectin levels and biochemical markers, particularly lipoproteins and suggested that SNP +276G>T was related to an independent effect on adiponectin levels and on lipoprotein metabolism[11]. On the contrary, adiponectin genetic variants and SNP +276G>T was associated with increasing susceptibility of type 2 diabetes and plasma glucose impairment[12]. The interesting study by Mohammadzadeh et al.[1] suggests that SNP of ADIPOQ +276G>T should be related to susceptibility to glucose metabolism, while indirectly to lipid metabolism and fat-related cardiovascular damage.

Project description:The development of high-throughput sequencing technologies is dramatically increasing the use of single nucleotide polymorphisms (SNPs) across the field of genetics, but most parentage studies of wild populations still rely on microsatellites. We developed a bioinformatic pipeline for identifying SNP panels that are informative for parentage analysis from restriction site-associated DNA sequencing (RADseq) data. This pipeline includes options for analysis with or without a reference genome, and provides methods to maximize genotyping accuracy and select sets of unlinked loci that have high statistical power. We test this pipeline on small populations of Mexican gray wolf and bighorn sheep, for which parentage analyses are expected to be challenging due to low genetic diversity and the presence of many closely related individuals. We compare the results of parentage analysis across SNP panels generated with or without the use of a reference genome, and between SNPs and microsatellites. For Mexican gray wolf, we conducted parentage analyses for 30 pups from a single cohort where samples were available from 64% of possible mothers and 53% of possible fathers, and the accuracy of parentage assignments could be estimated because true identities of parents were known a priori based on field data. For bighorn sheep, we conducted maternity analyses for 39 lambs from five cohorts where 77% of possible mothers were sampled, but true identities of parents were unknown. Analyses with and without a reference genome produced SNP panels with ≥95% parentage assignment accuracy for Mexican gray wolf, outperforming microsatellites at 78% accuracy. Maternity assignments were completely consistent across all SNP panels for the bighorn sheep, and were 74.4% consistent with assignments from microsatellites. Accuracy and consistency of parentage analysis were not reduced when using as few as 284 SNPs for Mexican gray wolf and 142 SNPs for bighorn sheep, indicating our pipeline can be used to develop SNP genotyping assays for parentage analysis with relatively small numbers of loci.

Project description:BackgroundGenome-wide association studies (GWAS) identify disease-associations for single-nucleotide-polymorphisms (SNPs) from scattered genomic-locations. However, SNPs frequently reside on several different SNP-haplotypes, only some of which may be disease-associated. This circumstance lowers the observed odds-ratio for disease-association.Methodology/principal findingsHere we develop a method to identify the two SNP-haplotypes, which combine to produce each person's SNP-genotype over specified chromosomal segments. Two multiple sclerosis (MS)-associated genetic regions were modeled; DRB1 (a Class II molecule of the major histocompatibility complex) and MMEL1 (an endopeptidase that degrades both neuropeptides and β-amyloid). For each locus, we considered sets of eleven adjacent SNPs, surrounding the putative disease-associated gene and spanning ∼200 kb of DNA. The SNP-information was converted into an ordered-set of eleven-numbers (subject-vectors) based on whether a person had zero, one, or two copies of particular SNP-variant at each sequential SNP-location. SNP-strings were defined as those ordered-combinations of eleven-numbers (0 or 1), representing a haplotype, two of which combined to form the observed subject-vector. Subject-vectors were resolved using probabilistic methods. In both regions, only a small number of SNP-strings were present. We compared our method to the SHAPEIT-2 phasing-algorithm. When the SNP-information spanning 200 kb was used, SHAPEIT-2 was inaccurate. When the SHAPEIT-2 window was increased to 2,000 kb, the concordance between the two methods, in both of these eleven-SNP regions, was over 99%, suggesting that, in these regions, both methods were quite accurate. Nevertheless, correspondence was not uniformly high over the entire DNA-span but, rather, was characterized by alternating peaks and valleys of concordance. Moreover, in the valleys of poor-correspondence, SHAPEIT-2 was also inconsistent with itself, suggesting that the SNP-string method is more accurate across the entire region.Conclusions/significanceAccurate haplotype identification will enhance the detection of genetic-associations. The SNP-string method provides a simple means to accomplish this and can be extended to cover larger genomic regions, thereby improving a GWAS's power, even for those published previously.

Project description:Summary In this work, we developed a simple and robust assay to rapidly detect SNPs in nucleic acid samples. Our approach combines loop-mediated isothermal amplification (LAMP)-based target amplification with fluorescent probes to detect SNPs with high specificity. A competitive “sink” strand preferentially binds to non-SNP amplicons and shifts the free energy landscape to favor specific activation by SNP products. We demonstrated the broad utility and reliability of our SNP-LAMP method by detecting three distinct SNPs across the human genome. We also designed an assay to rapidly detect highly transmissible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants from crude biological samples. This work demonstrates that competitive SNP-LAMP is a powerful and universal method that could be applied in point-of-care settings to detect any target SNP with high specificity and sensitivity. We additionally developed a publicly available web application for researchers to design SNP-LAMP probes for any target sequence of interest. Graphical abstract Highlights • A simple and rapid assay to detect specific SNPs in complex nucleic acid samples• Approach leverages competitive probes to specifically detect SNP over non-SNP sequences• Demonstrated utility across diverse targets and sample types• Web application for researchers to design SNP-LAMP probes for any target of interest Motivation Single-nucleotide polymorphisms (SNPs) are the most common source of genetic variation between individuals and have implications in human disease, pathogen drug resistance, and agriculture. SNPs are often detected using DNA sequencing or PCR, both of which can be difficult to deploy for on-site testing or in low-resource settings. There is a need for new SNP detection methods that can be performed rapidly without advanced laboratory equipment or a cold supply chain. Detecting single-nucleotide polymorphisms (SNPs) is important for understanding human disease, the emergence of pathogen variants, and the application of genetic agricultural breeding programs. Hyman et al. develop a simple and rapid assay to detect SNPs in complex nucleic acid samples. A web-based tool allows researchers to design custom SNP probes.

Dataset Information

Genetic Characterization of Cupped Oyster Resources in Europe Using Informative Single Nucleotide Polymorphism (SNP) Panels.

Publications

Genetic Characterization of Cupped Oyster Resources in Europe Using Informative Single Nucleotide Polymorphism (SNP) Panels.

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